Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve.

Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a 'reversed manner' may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural anti-predation trait (burrowing depth) of the marine bivalve Macoma balthica can be used as an indicator of the change in population size over the year to come. The per capita population growth rate between years t and t+1 correlated strongly with the proportion of individuals living in the dangerous top 4 cm layer of the sediment in year t: the more individuals in the top layer, the steeper the population decline. This is consistent with the prediction based on optimal foraging theory that animals with poor prospects should accept greater risks of predation. This study is among the first to document fitness forecasting in animals.